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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Diagnosis of Alzheimer's disease for general practitioners: screening instruments and early symptoms]
1Servicio de Neuropsicología (SIREN) del Instituto Universitario CEMIC. rallegri@cemic.edu.ar
Abstract:
Despite the increasing prevalence and the potential benefits of early identification, dementias continue to be under-diagnosed. By some estimates, fewer than half of all dementia patients have been diagnosed. AD is particularly under-diagnosed in primary care settings perhaps because patients with early AD may appear entirely appropriate in the context of a brief office visit. This, coupled with increasingly abbreviated office visits and the lack of routine use of mental status exams, make identification of cognitive deficit challenging in the primary care setting. Detection of these patients must be made by the general practitioners, who must know the possibilities to detect and guide the study of them. Patients' screening must include discrimination of forgetfulness and use of mini mental examination. Once the cognitive impairment is suspected we need to continue with neuropsychological assessment for cognitive profile, ancillary studies and CT scan to exclude structural diseases. The appropriate knowledge and training of general practitioners will allow the early diagnosis of these patients and the beginning of preventive actions and adequate symptomatic treatment.
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